Support vector fuzzy linear regression with fuzzy error

In this article, an approach for fitting a fuzzy linear regression model based on support vectors is presentedwhen the response variable, model parameters and errors are considered as fuzzy numbers.In this method, the objective function is based on the sum of the absolute values ​​of the distances of the hypothetical points to the non-parallel border hyperplanes. The presented model has good robustness to the presence of outlier data. The proposed model has been compared with some other models based on three goodness of fit indices.